Case Study: You need to build a tablet based app that is a shopping assistant. When I enter the store, I pick it up and it has the digital catalogue with current inventory status based on live POS feed (so it does not show anything that is stocked out). The digital catalogue is searchable using conversational interface (assume you have the NLP algo available for this). When I choose an item, it shows me similar items (which are identified based on image similarity analysis, you have an algo for it but you need to deploy it for weekly refresh of the similarity dataset) and items which go well together (based on mining past data, you have an algo for it but you need to deploy it for weekly refresh of the dataset). It also has an AR layer which can guide me to the item, and show what is nearby in same isle etc. and give instant offers etc. 1. What is broad architecture for this and choice of tech stack? 2. How will you structure this as a project and what will be team responsibility allocation and timelines?

1. Confidential Version 1.0
Case Study Exercise
Build a tablet based app that is a shopping assistant.

2. Overview
You need to build a tablet based app that is a shopping assistant. When I enter the store, I pick it up and it
has the digital catalogue with current inventory status based on live POS feed (so it does not show
anything that is stocked out). The digital catalogue is searchable using conversational interface (assume
you have the NLP algo available for this). When I choose an item, it shows me similar items (which are
identified based on image similarity analysis, you have an algo for it but you need to deploy it for weekly
refresh of the similarity dataset) and items which go well together (based on mining past data, you have
an algo for it but you need to deploy it for weekly refresh of the dataset). It also has an AR layer which can
guide me to the item, and show what is nearby in same isle etc. and give instant offers etc.
1. What is broad architecture for this and choice of tech stack?
2. How will you structure this as a project and what will be team responsibility allocation and timelines?

3. Problems to solve or components
1
Tablet interface for customer.
2
DAM(Digital asset management)
3
Speech to text
4
Recommendation Engine
5
Team Responsibility & Allocation

4. 01 Tablet interface for
customer.
- React native (can be port into both android and iOS
platforms)
- For VR we should be building it native.
- SDKs are as follows:
- Analytics
- Wikitude for VR
- VIPER architecture(will be dynamic enough)
QUICK TIP
Try right clicking on a photo and
using "Replace Image" to show
your own photo.

5. 02 Digital asset management
(DAM)
Key DAM Requirements:
- Ingest
- Metadata extraction
- Create renditions
- Build the catalog
- Enable rich search
- Manage storage lifecycle
- Provide efficient delivery of media assets

6. Digital Asset Management
(DAM)
Tech Stack:
- AWS SNS AWS Lambda - AWS S3
- AWS SQS - AWS DynamoDB/MongoDB
- Ruby/Go (AWS Elastic Beanstalk ) - AWS Cloudsearch/Elasticsearch
Ingest
Processing

7. Weekly refresh of the similarity dataset:

8. 03 Speech to text
Our solution uses 2 AWS Lambda functions, speaker
recognition, context switched response tree. This is all
tied together through aws sdk for app, using the Alexa
Skill Set and Alexa Voice Service

9. 04 Recommendation Engine
Our solution uses 2 AWS Lambda functions, speaker
recognition, context switched response tree. This is all
tied together through aws sdk for app, using the Alexa
Skill Set and Alexa Voice Service

10. 05 Team
Responsibility &
Allocation
3-4 months project for first rollout.
2 weeks sprints with demos and feedback.
CI and CD pipelines would be must
GIT as SCM
Feature Branching Strategy
APP and UI/UX Team
4 + 1
This team would be primarly
working on mock
APIs(provided by service team
to work on), App UI/UX, AR
implementation
ML and NLP team(Data Sceince)
3
ML and NLP team would be
working on training data set,
creating workflows, setting
pipelines for image feature
extraction
Backend team
8
2 - DAM
3 - API gateways and
contracts
3 - Core system(DB, )

11. Thank you.